Privacy, modesty, hospitality, and the design of Muslim homes: A literature review

Traditional Islamic teachings and traditions involve guidelines that have direct applications in the domestic sphere. The principles of privacy, modesty, and hospitality are central to these guidelines; each principle has a significant effect on the design of Muslim homes, as well as on the organization of space and domestic behaviors within each home. This paper reviews literature on the privacy, modesty, and hospitality within Muslim homes. Nineteen publications from 1986 to 2013 were selected and analyzed for content related to the meaning of privacy, modesty, and hospitality in Islam and the design of Muslim homes. Despite the commonly shared guidelines for observing privacy, modesty, and hospitality within each home, Muslims living in different countries are influenced by cultural factors that operate within their country of residence. These factors help to shape the architectural styles and use of space within Muslim homes in different ways. Awareness of the multifactorial nature of the influences on the Muslim perception of home and the use of space is necessary for architects, building designers, engineers, and builders to be properly equipped to meet the needs of clients.

Toward making inroads in reducing the disparity of lung health in Australian Indigenous and New Zealand Maori children

Globally, Indigenous populations, which include Aboriginal and Torres Strait islanders in Australia and Māori people in New Zealand (NZ), have poorer health than their non-Indigenous counterparts. Indigenous peoples worldwide face substantial challenges in poverty, education, employment, housing and disconnection from ancestral lands. While addressing social determinants of health is a priority, solving clinical issues is equally important. Indeed, ignoring the latter until social issues improve risks further disparity as this may take generations. A systematic overview of interventions addressing social determinants of health found a striking lack of reliable evaluations.Where evidence was available, health improvement associated with interventions was modest or uncertain. 10 Thus advances in healthcare remain essential and these require the best evidence available in 11 preventing and managing common illnesses, including respiratory illnesses.

Cytokine secretion in macrophages : SNAREs, Rabs and membrane trafficking

Macrophages have the capacity to rapidly secrete a wide range of inflammatory mediators that influence the development and extent of an inflammatory response. Newly synthesized and/or preformed stored cytokines and other inflammatory mediators are released upon stimulation, the timing, and volume of which is highly regulated. To finely tune this process, secretion is regulated at many levels; at the level of transcription and translation and post-translationally at the endoplasmic reticulum (ER), Golgi, and at or near the cell surface. Here, we discuss recent advances in deciphering these cytokine pathways in macrophages, focusing on recent discoveries regarding the cellular machinery and mechanisms implicated in the synthesis, trafficking, and secretion of cytokines. The specific roles of trafficking machinery including chaperones, GTPases, cytoskeletal proteins, and SNARE membrane fusion proteins will be discussed.

Development of an evidence-based symptom checklist for symptoms of recurrence in women with endometrial cancer

Objective Women treated for endometrial cancer currently commonly attend clinic-based follow-up examinations for up to five years. This is based on little evidence and alternative models need to be investigated. This study aimed to identify currently available symptom checklists, determine the comprehensiveness of identified checklists, and generate an updated list of symptoms potentially associated with a recurrence of endometrial cancer for future testing within a prospective study. Methods/materials We conducted a systematic review of the literature extracting; routine follow-up schedules; proportion of patients with symptomatic or asymptomatic recurrence; symptoms of recurrence; prevalence of these symptoms at recurrence. Results Overall, three previous checklists, and 12 retrospective studies were identified meeting the selection criteria. The average rate of recurrence across the studies was 13% (range 3%-19%). The proportion of patients identified with a symptomatic recurrence varied widely (overall average 67%;range 41% to 91%). The most commonly reported symptoms were vaginal bleeding (25%), pain [not further described] (16%) and abdominal pain and/or discomfort and swelling (15%) which combined, represented 56% of the total reported symptoms. The three previous checklists listed 14 and this review identified an additional 24 symptoms (e.g. vaginal discharge, leg pain, constipation, headache and self-detected mass) not previously identified. Conclusion The newly developed symptom checklist expands previous ones, by an additional 24 symptoms. It will be used in a prospective cohort study to assess whether it is sensitive and specific enough to identify recurrence compared to current standard follow-up examinations.

An external field prior for the hidden Potts model with application to cone-beam computed tomography

In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for representing spatial prior information as an external field in a hidden Potts model is introduced. This prior distribution over the latent pixel labels is a mixture of Gaussian fields, centred on the positions of the objects at a previous point in time. It is particularly applicable in longitudinal imaging studies, where the manual segmentation of one image can be used as a prior for automatic segmentation of subsequent images. The method is demonstrated by application to cone-beam computed tomography (CT), an imaging modality that exhibits distortions in pixel values due to X-ray scatter. The external field prior results in a substantial improvement in segmentation accuracy, reducing the mean pixel misclassification rate for an electron density phantom from 87% to 6%. The method is also applied to radiotherapy patient data, demonstrating how to derive the external field prior in a clinical context.

A meshless method based on Point Interpolation Method (PIM) for the space fractional diffusion equation

This paper aims to develop a meshless approach based on the Point Interpolation Method (PIM) for numerical simulation of a space fractional diffusion equation. Two fully-discrete schemes for the one-dimensional space fractional diffusion equation are obtained by using the PIM and the strong-forms of the space diffusion equation. Numerical examples with different nodal distributions are studied to validate and investigate the accuracy and efficiency of the newly developed meshless approach.

Costs and benefits of ivory-billed woodpecker re-discovery

Several years ago, the purported re-discovery of the ivory-billed woodpecker (Campephilus principalis) in eastern Arkansas generated lively discussion in renowned scientific journals. The debate concerned both the central question of whether the bird videotaped in April 2004 really was an ivorybilled woodpecker (eg Fitzpatrick et al. 2005; Sibley et al. 2006) and the controversy around the resulting species recovery plan and its costs (McKelvey et al. 2008; Dalton 2010): was $14 million pointlessly spent?

Efficient minimax strategies for square loss games

We consider online prediction problems where the loss between the prediction and the outcome is measured by the squared Euclidean distance and its generalization, the squared Mahalanobis distance. We derive the minimax solutions for the case where the prediction and action spaces are the simplex (this setup is sometimes called the Brier game) and the \ell_2 ball (this setup is related to Gaussian density estimation). We show that in both cases the value of each sub-game is a quadratic function of a simple statistic of the state, with coefficients that can be efficiently computed using an explicit recurrence relation. The resulting deterministic minimax strategy and randomized maximin strategy are linear functions of the statistic.

Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation

Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

Gaming well: Links between videogames and flourishing mental health

This paper is a review of the state of play of research linking videogaming and flourishing, and explores the role of videogames and technology to improve mental health and well-being. Its purpose is to develop understandings about the positive intersection of gaming and well-being, to document evidence regarding links between videogames and positive mental health, and to provide guidelines for use by other researchers as they design and use tools and games to improve mental health and well-being. Using Huppert's (Huppert and So, 2013) proposition that to flourish is more than the absence of mental disorder but rather a combination of feeling good and functioning effectively, resulting in high levels of mental well-being, and Seligman's (Seligman, 2011) PERMA theory of well-being, the paper identifies strengths in existing games that generate positive affect, positive functioning, and positive social functioning, contributing to, and supporting mental health and well-being.

Curiosity driven reinforcement learning for motion planning on humanoids

Most previous work on artificial curiosity (AC) and intrinsic motivation focuses on basic concepts and theory. Experimental results are generally limited to toy scenarios, such as navigation in a simulated maze, or control of a simple mechanical system with one or two degrees of freedom. To study AC in a more realistic setting, we embody a curious agent in the complex iCub humanoid robot. Our novel reinforcement learning (RL) framework consists of a state-of-the-art, low-level, reactive control layer, which controls the iCub while respecting constraints, and a high-level curious agent, which explores the iCub's state-action space through information gain maximization, learning a world model from experience, controlling the actual iCub hardware in real-time. To the best of our knowledge, this is the first ever embodied, curious agent for real-time motion planning on a humanoid. We demonstrate that it can learn compact Markov models to represent large regions of the iCub's configuration space, and that the iCub explores intelligently, showing interest in its physical constraints as well as in objects it finds in its environment.

A semi-alternating direction method for a 2-D fractional FitzHugh–Nagumo monodomain model on an approximate irregular domain

A FitzHugh-Nagumo monodomain model has been used to describe the propagation of the electrical potential in heterogeneous cardiac tissue. In this paper, we consider a two-dimensional fractional FitzHugh-Nagumo monodomain model on an irregular domain. The model consists of a coupled Riesz space fractional nonlinear reaction-diffusion model and an ordinary differential equation, describing the ionic fluxes as a function of the membrane potential. Secondly, we use a decoupling technique and focus on solving the Riesz space fractional nonlinear reaction-diffusion model. A novel spatially second-order accurate semi-implicit alternating direction method (SIADM) for this model on an approximate irregular domain is proposed. Thirdly, stability and convergence of the SIADM are proved. Finally, some numerical examples are given to support our theoretical analysis and these numerical techniques are employed to simulate a two-dimensional fractional Fitzhugh-Nagumo model on both an approximate circular and an approximate irregular domain.

Numerical algorithms for time-fractional subdiffusion equation with second-order accuracy

This article aims to fill in the gap of the second-order accurate schemes for the time-fractional subdiffusion equation with unconditional stability. Two fully discrete schemes are first proposed for the time-fractional subdiffusion equation with space discretized by finite element and time discretized by the fractional linear multistep methods. These two methods are unconditionally stable with maximum global convergence order of $O(\tau+h^{r+1})$ in the $L^2$ norm, where $\tau$ and $h$ are the step sizes in time and space, respectively, and $r$ is the degree of the piecewise polynomial space. The average convergence rates for the two methods in time are also investigated, which shows that the average convergence rates of the two methods are $O(\tau^{1.5}+h^{r+1})$. Furthermore, two improved algorithms are constrcted, they are also unconditionally stable and convergent of order $O(\tau^2+h^{r+1})$. Numerical examples are provided to verify the theoretical analysis. The comparisons between the present algorithms and the existing ones are included, which show that our numerical algorithms exhibit better performances than the known ones.

High order unconditionally stable difference schemes for the Riesz space-fractional telegraph equation

In this paper, a class of unconditionally stable difference schemes based on the Pad´e approximation is presented for the Riesz space-fractional telegraph equation. Firstly, we introduce a new variable to transform the original dfferential equation to an equivalent differential equation system. Then, we apply a second order fractional central difference scheme to discretise the Riesz space-fractional operator. Finally, we use (1, 1), (2, 2) and (3, 3) Pad´e approximations to give a fully discrete difference scheme for the resulting linear system of ordinary differential equations. Matrix analysis is used to show the unconditional stability of the proposed algorithms. Two examples with known exact solutions are chosen to assess the proposed difference schemes. Numerical results demonstrate that these schemes provide accurate and efficient methods for solving a space-fractional hyperbolic equation.

A fast semi-implicit difference method for a nonlinear two-sided space-fractional diffusion equation with variable diffusivity coefficients

In this paper, we derive a new nonlinear two-sided space-fractional diffusion equation with variable coefficients from the fractional Fick’s law. A semi-implicit difference method (SIDM) for this equation is proposed. The stability and convergence of the SIDM are discussed. For the implementation, we develop a fast accurate iterative method for the SIDM by decomposing the dense coefficient matrix into a combination of Toeplitz-like matrices. This fast iterative method significantly reduces the storage requirement of O(n2)O(n2) and computational cost of O(n3)O(n3) down to n and O(nlogn)O(nlogn), where n is the number of grid points. The method retains the same accuracy as the underlying SIDM solved with Gaussian elimination. Finally, some numerical results are shown to verify the accuracy and efficiency of the new method.